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Various approaches toward the development of sustainable software systems have been proposed by the requirements engineering community over the last decade. We conducted a systematic mapping study, analyzed 55 publications, and identified 29 approaches that have been published since the year 2000. We analyzed how the approaches evolved over time and how the publications and authors are influenced by each other. Furthermore, the approaches are analyzed in terms of their supported requirements engineering activities, along with the evidence provided in the publications. Additionally, we also analyzed which sustainability definitions have been used, if an iterative application of the approaches is discussed, and if the approaches also provide a tool-support for practitioners. We noticed an increase of publications on requirements engineering approaches toward sustainability in the last years, whereas a majority discuss sustainability based on the same multi-dimensional concept. Although different case studies have been already conducted, we noticed a lack of an industrial application. Our main findings concern the need of an evaluation on how the proposed requirements engineering approaches can also be applied in agile software development processes. Additionally, we also promote the development of supporting software tools to support practitioners in adapting the proposed approaches. [ABSTRACT FROM AUTHOR]

Quality requirements deal with how well a product should perform the intended functionality, such as start-up time and learnability. Researchers argue they are important and at the same time studies indicate there are deficiencies in practice. Our goal is to review the state of evidence for quality requirements. We want to understand the empirical research on quality requirements topics as well as evaluations of quality requirements solutions. We used a hybrid method for our systematic literature review. We defined a start set based on two literature reviews combined with a keyword-based search from selected publication venues. We snowballed based on the start set. We screened 530 papers and included 84 papers in our review. Case study method is the most common (43), followed by surveys (15) and tests (13). We found no replication studies. The two most commonly studied themes are (1) differentiating characteristics of quality requirements compared to other types of requirements, (2) the importance and prevalence of quality requirements. Quality models, QUPER, and the NFR method are evaluated in several studies, with positive indications. Goal modeling is the only modeling approach evaluated. However, all studies are small scale and long-term costs and impact are not studied. We conclude that more research is needed as empirical research on quality requirements is not increasing at the same rate as software engineering research in general. We see a gap between research and practice. The solutions proposed are usually evaluated in an academic context and surveys on quality requirements in industry indicate unsystematic handling of quality requirements. [ABSTRACT FROM AUTHOR]

Welcome to this special issue that includes papers on the latest advances in Requirements Engineering (RE). As new software systems are developed, they can impact our society, economy and environment, and software requirement engineers should consider the implications on sustainability when designing software requirements. [Extracted from the article]

Requirements engineering (RE) has established itself as a core software engineering discipline. It is well acknowledged that good RE leads to higher quality software and considerably reduces the risk of failure or budget-overspending of software development projects. It is of vital importance to train future software engineers in RE and educate future requirements engineers to adequately manage requirements in various projects. To this date, there exists no central concept of what RE education shall comprise. To lay a foundation, we report on a systematic literature review of the field and provide a systematic map describing the current state of RE education. Doing so allows us to describe how the educational landscape has changed over the last decade. Results show that only a few established author collaborations exist and that RE education research is predominantly published in venues other than the top RE research venues (i.e., in venues other than the RE conference and journal). Key trends in RE instruction of the past decade include involvement of real or realistic stakeholders, teaching predominantly elicitation as an RE activity, and increasing student factors such as motivation or communication skills. Finally, we discuss open opportunities in RE education, such as training for security requirements and supply chain risk management, as well as developing a pedagogical foundation grounded in evidence of effective instructional approaches. [ABSTRACT FROM AUTHOR]

Requirements engineering (RE) has attracted a great deal of attention from researchers and practitioners in recent years. Requirements engineering education (REE) is therefore an important undertaking if the field is to have professionals who are capable of successfully accomplishing software projects. This increasing interest demands that academia should provide software engineering students with a solid foundation in the subject matter. This paper aims to identify and to present the current research on REE that is available at present, and to select useful approaches and needs for future research. A systematic mapping study was therefore performed to classify the selected studies into five classification criteria: research type, empirical type, contribution type, RE activity, and curricula. A total of 79 papers were selected and classified according to these criteria. The results of this systematic mapping study are discussed, and a list of advice obtained from the REE literature for instructors is provided. [ABSTRACT FROM AUTHOR]

Big data analytics technologies are rapidly expanding across all industry sectors as organisations try to make analytics an integral part of their everyday decision-making. Although there are many software tools and libraries to assist analysts and software engineers in developing solutions, organisations are looking for flexible analytics platforms that can address their specific objectives and requirements. To minimise costs, such platforms also need to co-exist with existing IT infrastructures and reuse knowledge and resources already accumulated within the organisation. To address such needs, this paper proposes the Data Analytics Solution Engineering (DASE) framework—a knowledge-driven approach supported by semantic web technologies for requirements engineering, design and development of new data analytics platforms. It includes a meta-model that captures data analytics platform requirements via a Knowledge Base, a set of guidelines that organisations can follow in engineering data analytics platforms and a reference architecture that demonstrates how to use these guidelines. We evaluate the DASE framework through two case studies and demonstrate how it can facilitate knowledge-based and requirements-driven data analytics platform engineering. The resulting data analytics platforms are observed to be user friendly, easy to maintain and flexible in handling changes to requirements. This work contributes to the body of knowledge in knowledge-driven requirements engineering, and data analytics platform engineering by providing a meta-model and a reference architecture that can be tailored to different analytics application domains. [ABSTRACT FROM AUTHOR]

As software engineering (SE) practitioners, we can help society by using our communities of experts to address a software need of a socially conscious organization. Doing so can benefit society in the locale of a SE conference and provide access to international experts for local organizations. Furthermore, established SE researchers as well as practitioners and students have the opportunity for a unique learning experience. While the SE community has already realized the importance of addressing human values and promoting social good objectives in software development, we are unaware of previous attempts to leverage SE conferences for this activity. Conferences present an opportunity to enjoy the assembly of SE practitioners, researchers, and students for the purpose of a philanthropic endeavor. Over the past four years of running a "Requirements Engineering for Social Good" event called RE Cares, co-located with the International Conference on Requirements Engineering, we worked with the stakeholders local to the conference venue. We selected stakeholders who would not necessarily have ready access to requirements engineering, software design, and development expertise otherwise, to build software targeting "good causes." In the last two years, this event was altered to adapt to the constraints induced by COVID-19, moving to a hybrid mode and changing many of its practices accordingly. This paper summarizes and generalizes our experiences, discussing our lessons learned in the context of the pandemic and beyond and providing a framework for conducting similar social contribution in any SE conferences in general. [ABSTRACT FROM AUTHOR]

Traceability links recovery (TLR) has been a topic of interest for many years. However, TLR approaches are based on the latent semantics of the software artifacts, and are not equipped to deal with software artifacts that lack those inherent semantics, such as BPMN models. The aim of this work is to enhance TLR approaches in BPMN models by incorporating the linguistic particularities of BPMN models into the TLR process. Our approach runs through a threefold contribution: (1) we identify the particularities of BPMN models; (2) we describe how to leverage the particularities; and (3) we build three variants of the best exploratory TLR approach which specifically cater to BPMN models. The approach is evaluated through both an academic case study and a real-world industrial case study. The results show that incorporating the particularities of BPMN into the TLR process leads the specific approach to improve the traceability results obtained by generalist approaches, maintaining precision levels and improving recall. The novel findings of this paper suggest that there is a benefit in researching and taking in account the particularities of the different kinds of models in order to optimize the results of TLR between requirements and models, instead of relying on generalist approaches. [ABSTRACT FROM AUTHOR]

Traceability is crucial for many activities in software and systems engineering including monitoring the development progress, and proving compliance with standards. In practice, the use and maintenance of trace links are challenging as artifacts undergo constant change, and development takes place in distributed scenarios with multiple collaborating stakeholders. Although traceability management in general has been addressed in previous studies, there is a need for empirical insights into the collaborative aspects of traceability management and how it is situated in existing development contexts. The study reported in this paper aims to close this gap by investigating the relation of collaboration and traceability management, based on an understanding of characteristics of the development effort. In our multiple exploratory case study, we conducted semi-structured interviews with 24 individuals from 15 industrial projects. We explored which challenges arise, how traceability management can support collaboration, how collaboration relates to traceability management approaches, and what characteristics of the development effort influence traceability management and collaboration. We found that practitioners struggle with the following challenges: (1) collaboration across team and tool boundaries, (2) conveying the benefits of traceability, and (3) traceability maintenance. If these challenges are addressed, we found that traceability can facilitate communication and knowledge management in distributed contexts. Moreover, there exist multiple approaches to traceability management with diverse collaboration approaches, i.e., requirements-centered, developer-driven, and mixed approaches. While traceability can be leveraged in software development with both agile and plan-driven paradigms, a certain level of rigor is needed to realize its benefits and overcome challenges. To support practitioners, we provide principles of collaborative traceability management. The main contribution of this paper is empirical evidence of how culture, processes, and organization impact traceability management and collaboration, and principles to support practitioners with collaborative traceability management. We show that collaboration and traceability management have the potential to be mutually beneficial—when investing in one, also the other one is positively affected. [ABSTRACT FROM AUTHOR]

Nowadays, the growing importance of modelling in software engineering is without a doubt reinforced by the blossoming of model-driven architecture (MDA). In this trend, MDA could be considered the most convenient approach to integrate the modelling process in data warehousing projects. On the other hand, decision-makers are usually unable to express their business needs in a concise way that allows getting a valid data warehouse (DW), mainly due to the lack of standard methodologies and tools devoted to supporting this situation. This fact might expand the gap between the business world and the IT world and causes troublesome difficulties to interpret and model DW requirements. Moreover, applying MDA for this kind of project requires using new tools to avoid this drawback. In this paper, we provide an MDA framework to design DW requirements and generate afterwards the multidimensional schema. The framework is based on UML profiles and presents to decision-makers a graphical tool for modelling their strategic visions in order to build the system-to-be. Besides, the proposal allows for dealing with data historization and metadata in the generated multidimensional model to perform properly the extract transform load process. [ABSTRACT FROM AUTHOR]

With the rise in initiatives such as software ecosystems and Internet of Things (IoT), developing web Application Programming Interfaces (web APIs) has become an increasingly common practice. One main concern in developing web APIs is that they expose back-end systems and data toward clients. This exposure threatens critical non-functional requirements, such as the security of back-end systems, the performance of provided services, and the privacy of communications with clients. Although dealing with non-functional requirements during software design has been long studied, there is still no framework to specifically assist software developers in addressing these requirements in web APIs. In this paper, we introduce Rational API Designer (RAPID), an open-source assistant that advises on designing non-functional requirements in the architecture of web APIs. We have equipped RAPID with a broad range of expert knowledge about API design, systematically collected and extracted from the literature. The API design knowledge has been encoded as a set of 156 rules using the Non-Functional Requirements (NFR) multi-valued logic, a formal framework commonly used to describe non-functional and functional requirements of software systems. RAPID uses the encoded knowledge in a stepwise inference procedure to arrive from a given requirement, to a set of design alternatives to a final recommendation for a given API design specification. Seven well-experienced software engineers have blindly evaluated the accuracy of RAPID's consultations over seven different cases of web API design and on providing design guidelines for thirty design questions. The results of the evaluation show that RAPID's recommendations meet acceptable standards of the majority of the evaluators 73.3% of the time. Moreover, analysis of the evaluators' comments suggests that more than one-third of the unacceptable ratings (33.8%) given to RAPID's answers are due to valid but incomplete design guidelines. We thus expect that the accuracy of the consultations will increase as RAPID's knowledge of API design is extended and refined. [ABSTRACT FROM AUTHOR]

Security is nowadays an indispensable requirement in software systems. Traditional software engineering processes focus primarily on business requirements, leaving security as an afterthought to be addressed via generic 'patched-on' defensive mechanisms. This approach is insufficient, and software systems need to have security functionality engineered within in a similar fashion as ordinary business functional requirements. Functional security requirements need to be elicited, analyzed, specified and validated at the early stages of the development life cycle. If the functional security requirements were not properly validated, then there is a risk of developing a system that is insecure, deeming it unusable. Acceptance testing is an effective technique to validate requirements. However, an ad hoc approach to develop acceptance tests will suffer the omission of important tests. This paper presents a systematic approach to develop executable acceptance tests that is specifically geared for model-based secure software engineering processes. The approach utilizes early-stage artifacts, namely misuse case and domain models, and robustness diagrams. The feasibility of the proposed approach is demonstrated by applying it to a real-world system. The results show that a comprehensive set of security acceptance tests can be developed based upon misuse case models for early-stage validation of functional security requirements. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the potential benefits of utilizing natural language semantics in automated traceability link retrieval. In particular, we evaluate the performance of a wide spectrum of semantically enabled information retrieval methods in capturing and presenting requirements traceability links in software systems. Our objectives are to gain more operational insights into these methods and to provide practical guidelines for the design and development of effective requirements tracing and management tools. To achieve our research objectives, we conduct an experimental analysis using three datasets from various application domains. Results show that considering more semantic relations in traceability link retrieval does not necessarily lead to higher quality results. Instead, a more focused semantic support, that targets specific semantic relations, is expected to have a greater impact on the overall performance of tracing tools. In addition, our analysis shows that explicit semantic methods, that exploit local or domain-specific sources of knowledge, often achieve a more satisfactory performance than latent methods, or methods that derive semantics from external or general-purpose knowledge sources. [ABSTRACT FROM AUTHOR]

A potential mathematical framework for machine learning is multi-linear algebra of the higher-order tensor that can reveal the relationships among multiple factors underlying the observations. Prioritizing the requirements of a project facilitates the process of requirements engineering and involves multifactors. Due to existing time constraints and budget related to projects, by prioritizing the requirements in an appropriate order we can select and apply them more accurately and this causes to increase the quality of software and customers’ satisfaction. In order to prioritize the requirements, there are many approaches that consider different parameters and different view point in their prioritization process. But as far as we know none of them considers the simultaneous effect among entities, namely functional requirements, non-functional requirements and stakeholders in their prioritization process. In this paper, we decided to consider the simultaneous effect among functional, non-functional requirements and stakeholders that have different preferences on requirements by modeling a three-order tensor. Then by applying multi-way analysis, we will obtain appropriate ordered lists of requirements. To evaluate our approach, a controlled experiment has been provided that compares the proposed approach with the state-of-the-art-based approach, analytic hierarchy process (AHP). The results show that our proposed approach outperforms AHP in terms of actual time consumption and ease of use while preserving the quality of the results obtained by our proposed approach. [ABSTRACT FROM AUTHOR]

Software engineering practice has shifted from the development of products in closed environments toward more open and collaborative efforts. Software development has become significantly interdependent with other systems (e.g. services, apps) and typically takes place within large ecosystems of networked communities of stakeholder organizations. Such software ecosystems promise increased innovation power and support for consumer-oriented software services at scale and are characterized by a certain openness of their information flows. While such openness supports project and reputation management, it also brings requirements engineering-related challenges within the ecosystem, such as managing dynamic, emergent contributions from the ecosystem stakeholders, as well as collecting their input while protecting their IP. In this paper, we report from a study of requirements communication and management practices within IBM®’s Collaborative Lifecycle Management® product development ecosystem. Our research used multiple methods for data collection, including interviews within several ecosystem actors, on-site participatory observation, and analysis of online project repositories. We chart and describe the flow of product requirements information through the ecosystem, how the open communication paradigm in software ecosystems provides opportunities for “just-in-time” RE—and which relies on emergent contributions from the ecosystem stakeholders—, as well as some of the challenges faced when traditional requirements engineering approaches are applied within such an ecosystem. More importantly, we discuss two tradeoffs brought about by the openness in software ecosystems: (1) allowing open, transparent communication while keeping intellectual property confidential within the ecosystem and (2) having the ability to act globally on a long-term strategy while empowering product teams to act locally to answer end users’ context-specific needs in a timely manner. A sufficient level of openness facilitates contributions of emergent stakeholders. The ability to include important emergent contributors early in requirements elicitation appears to be a crucial asset in software ecosystems. [ABSTRACT FROM AUTHOR]

Because of the large amount of effort it takes to manually trace requirements, automated traceability methods for mapping textual software engineering artifacts to each other and generating candidate links have received increased attention over the past 15 years. Automatically generated links, however, are viewed as candidates until human analysts confirm/reject them for the final requirements traceability matrix. Studies have shown that analysts are a fallible, but necessary, participant in the tracing process. There are two key measures guiding analyst work on the evaluation of candidate links: accuracy of analyst decision and efficiency of their work. Intuitively, it is expected that the more effort the analyst spends on candidate link validation, the more accurate the final traceability matrix is likely to be, although the exact nature of this relationship may be difficult to gauge outright. To assist analysts in making the best use of their time when reviewing candidate links, prior work simulated four possible behaviors and showed that more structured approaches save the analysts’ time/effort required to achieve certain levels of accuracy. However, these behavioral simulations are complex to run and their results difficult to interpret and use in practice. In this paper, we present a mathematical model for evaluating analyst effort during requirements tracing tasks. We apply this model to a simulation study of 12 candidate link validation approaches. The simulation study is conducted on a number of different datasets. In each study, we assume perfect analyst behavior (i.e., analyst always being correct when making a determination about a link). Under this assumption, we evaluate the estimated effort for the analyst and plot it against the accuracy of the recovered traceability matrix. The effort estimation model is guided by a parameter specifying the relationship between the time it takes an analyst to evaluate a presented link and the time it takes an analyst to discover a link not presented to her. We construct a series of effort estimations based on different values of the model parameter. We found that the analysts’ approach to candidate link validation—essentially the order in which the analyst examines presented candidate links—does impact the effort. We also found that the lowest ratio of the cost of finding a correct link from scratch over the cost of recognizing a correct link yields the lowest effort for all datasets, but that the lowest effort does not always yield the highest quality matrix. We finally observed that effort varies by dataset. We conclude that the link evaluation approach we call “Top 1 Not Yet Examined Feedback Pruning” was the overall winner in terms of effort and highest quality and, thus, should be followed by human analysts if possible. [ABSTRACT FROM AUTHOR]

Organizations developing software for critical sectors like aerospace, automotive, and medical systems need to apply process requirements coming from different sources: industrial standards, customer-provided requirements, and procedures from internal quality management systems. In these situations, software teams need to deal with complex sets of process requirements that govern different aspects of their work. This paper describes the development of a collaborative, web-based solution to improve access to process requirements. The solution makes use of semantic technologies to handle the context of process requirement. Requirements are contextualized by linking them to activities, tasks, and work products. With this tool, software engineers have a single point of access to all the applicable process requirements, avoiding the risk of missing relevant information. [ABSTRACT FROM AUTHOR]

This paper proposes an explicit definition of green software requirements and a tool to support their evaluation . The proposed evaluation tool describes the green efficiency by considering the energy consumption as the main aspect to be studied during the development stage. This approach consists of building a multiple regression model, by using a supervised learning algorithm, in order to reproduce the energy consumption pattern of devices at different workload circumstances. The energy consumption model is then deployed to estimate the impact of software applications based on their resource usage. Our work has been validated on desktop and mobile devices. The experiments show the effectiveness of the proposed energy profiling tool that provided relevant information on the energy consumption of software applications. [ABSTRACT FROM AUTHOR]

The increasing demand for complex and distributed software calls for novel software engineering methods and techniques, to create systems able to autonomously adapt to dynamically changing situations. In this paper, we present a framework for engineering requirements for adaptive software systems. The approach, called Tropos4AS, combines goal-oriented concepts and high-variability design methods. The Tropos4AS requirements model can be directly mapped to software prototypes with an agent-oriented architecture which can be executed for requirements validation and refinement. We give a comprehensive description of the framework, with conceptual models, modelling guidelines, and supporting tools. The applicability of the framework to requirements validation and refinement is illustrated through a case study. Two controlled experiments with subjects provide an empirical evaluation of the proposed modelling language, with statistical evidence of the effectiveness of the modelling approach for gathering requirements of adaptive systems. [ABSTRACT FROM AUTHOR]

Telos is a conceptual modeling language intended to capture software knowledge, such as software system requirements, domain knowledge, architectures, design decisions and more. To accomplish this, Telos was designed to be extensible in the sense that the concepts used to capture software knowledge can be defined in the language itself, instead of being built-in. This extensibility is accomplished through powerful metamodeling features, which proved very useful for interrelating heterogeneous models from requirements, model-driven software engineering, data integration, ontology engineering, cultural informatics and education. We trace the evolution of ideas and research results in the Telos project from its origins in the late eighties. Our account looks at the semantics of Telos, its various implementations and its applications. We also recount related research by other groups and the cross-influences of ideas thereof. We conclude with lessons learnt. [ABSTRACT FROM AUTHOR]

In software projects involving large and often distributed teams, requirements evolve through the collaboration of many stakeholders, supported by online tools such as mailing lists, bug tracking systems, or online discussion forums. In this collaboration, requirements typically evolve from initial ideas, through clarification, to the implementation of a stable requirement. Deviations from this expected course might indicate requirements that are poorly understood, need further negotiation, or better alignment with project goals. If not addressed timely, such problems can surface late in the development cycle with negative consequences such as rework, missed schedules, or overrun budget. This paper presents an approach that provides project managers' with timely awareness of such requirements-related risks, based on automatic analysis of stakeholders' online requirement communication. We describe a clarification classifier that automatically analyzes requirements communication in a project and detects clarification events, a catalog of clarification patterns, and a pattern matcher that suggests communication patterns based on our pattern catalog. Our approach has been empirically constructed and evaluated in a case study in the $$\hbox {IBM}^{\circledR }$$ Rational Team $$\hbox {Concert}^\circledR$$ project. We discuss the applicability of our approach in other projects as well as avenues for extending our pattern catalog toward a theory of clarification patterns. [ABSTRACT FROM AUTHOR]

Large-scale software applications are complex systems that involve a myriad of different concerns. Ideally, these concerns should be organized into separated and different modules, but often some of these concerns overlap and crosscut each other. Such a situation is problematic, as concerns are tangled and scattered into different modules; thus, design and source code become difficult to produce and maintain. The Modularity community has been addressing crosscutting concerns by developing techniques based on separation of concerns. This separation must be done as early as possible during software construction to obtain a more modular and consequently better maintainable software, where evolution is performed with less effort and the possibility of introducing unforeseen mistakes is minimal. In this paper, we propose a strategy to identify crosscutting concerns at requirements level, i.e., at early stages in the software development process, by using the Language Extended Lexicon. [ABSTRACT FROM AUTHOR]

Requirements engineering is one of the most important areas of software engineering because it enables practitioners to determine the characteristics and constraints of the software to be developed. Therefore, the requirements elicitation process aims to obtain a preliminary version of the requirements before their specification, but it is difficult to know if the elicited requirements have the desired attributes (i.e., these requirements are complete, correct, consistent, etc.) due to the nature of this process. There are some measures that allow requirements engineers to quantify certain aspects of the requirements elicitation process and its final product (i.e., the preliminary version of the requirements, also known as preliminary requirements), but there is no way of measuring and controlling the quality of the elicited preliminary requirements. With the aim of understanding, evaluating, and improving the activities of the requirements elicitation process, some of the existing measures for this process were analyzed and, consequently, a case study was conducted to define and implement a measurement program with a set of eight measures that are proposed in this study. This program is based on the ISO/IEC/IEEE 15939:2017—systems and software engineering—measurement process, an international standard that establishes a common process and framework for the measurement of systems and software. The measurement program corresponds to a lightweight implementation of the standard in the context of a small-sized software organization (where the size of the software staff is 11–50 people, the size of projects is 50,000–100,000 LOC, and the time spent on the projects is six to twelve months) and the obtained results showed a preliminary positive influence when obtaining high-quality preliminary requirements. [ABSTRACT FROM AUTHOR]

When developing or evolving software systems of non-trivial size, having the requirements properly documented is a crucial success factor. The time and effort required for creating and maintaining non-code artifacts are significantly influenced by the tools with which practitioners view, navigate and edit these artifacts. This is not only true for requirements, but for any artifacts used when developing or evolving systems. However, there is not much evidence about how practitioners actually work with artifacts and how well software tools support them. Therefore, we conducted an exploratory study based on 29 interviews with software practitioners to understand the current practice of presenting and manipulating artifacts in tools, how practitioners deal with the challenges encountered, and how these challenges affect the usability of the tools used. We found that practitioners typically work with several interrelated artifacts concurrently, less than half of these artifacts can be displayed entirely on a large screen, the artifact interrelationship information is often missing, and practitioners work collaboratively on artifacts without sufficient support. We identify the existing challenges of working with artifacts and discuss existing solutions proposed addressing them. Our results contribute to the body of knowledge about how practitioners work with artifacts when developing or evolving software, the challenges they are faced with, and the attempts to address these challenges. [ABSTRACT FROM AUTHOR]

Requirements analysis is the software engineering stage that is closest to the users' world. It also involves tasks that are knowledge intensive. Thus, the use of Bayesian networks (BNs) to model this knowledge would be a valuable aid. These probabilistic models could manage the imprecision and ambiguities usually present in requirements engineering (RE). In this work, we conduct a literature review focusing on where and how BNs are applied on subareas of RE in order to identify which gaps remain uncovered and which methods might engineers employ to incorporate this intelligent technique into their own requirements processes. The scarcity of identified studies (there are only 20) suggests that not all RE areas have been properly investigated in the literature. The evidence available for adopting BNs into RE is sufficiently mature yet the methods applied are not easily translatable to other topics. Nonetheless, there are enough studies supporting the applicability of synergistic cooperation between RE and BNs. This work provides a background for understanding the current state of research encompassing RE and BNs. Functional, non-functional and -ilities requirements artifacts are enhanced by the use of BNs. These models were obtained by interacting with experts or by learning from databases. The most common criticism from the point of view of BN experts is that the models lack validation, whereas requirements engineers point to the lack of a clear application method for BNs and the lack of tools for incorporating them as built-in help functions. [ABSTRACT FROM AUTHOR]

The growing complexity of software systems and the influence of software-supported decisions in our society sparked the need for software that is transparent, accountable, and trustworthy. Explainability has been identified as a means to achieve these qualities. It is recognized as an emerging non-functional requirement (NFR) that has a significant impact on system quality. Accordingly, software engineers need means to assist them in incorporating this NFR into systems. This requires an early analysis of the benefits and possible design issues that arise from interrelationships between different quality aspects. However, explainability is currently under-researched in the domain of requirements engineering, and there is a lack of artifacts that support the requirements engineering process and system design. In this work, we remedy this deficit by proposing four artifacts: a definition of explainability, a conceptual model, a knowledge catalogue, and a reference model for explainable systems. These artifacts should support software and requirements engineers in understanding the definition of explainability and how it interacts with other quality aspects. Besides that, they may be considered a starting point to provide practical value in the refinement of explainability from high-level requirements to concrete design choices, as well as on the identification of methods and metrics for the evaluation of the implemented requirements. [ABSTRACT FROM AUTHOR]

Goal models have been widely used in computer science to represent software requirements, business objectives, and design qualities. Existing goal modelling techniques, however, have shown limitations of expressiveness and/or tractability in coping with complex real-world problems. In this work, we exploit advances in automated reasoning technologies, notably satisfiability and optimization modulo theories (SMT/OMT), and we propose and formalize: (1) an extended modelling language for goals, namely the constrained goal model (CGM), which makes explicit the notion of goal refinement and of domain assumption, allows for expressing preferences between goals and refinements and allows for associating numerical attributes to goals and refinements for defining constraints and optimization goals over multiple objective functions, refinements, and their numerical attributes; (2) a novel set of automated reasoning functionalities over CGMs, allowing for automatically generating suitable refinements of input CGMs, under user-specified assumptions and constraints, that also maximize preferences and optimize given objective functions. We have implemented these modelling and reasoning functionalities in a tool, named CGM-Tool, using the OMT solver OptiMathSAT as automated reasoning backend. Moreover, we have conducted an experimental evaluation on large CGMs to support the claim that our proposal scales well for goal models with 1000s of elements. [ABSTRACT FROM AUTHOR]

The importance of prioritizing requirements stems from the fact that not all requirements can usually be met with available time and resource constraints. Efficient and trustworthy methods for prioritizing requirements are therefore in high demand. In this article, we present results of a systematic mapping study in order to appreciate the different considerations that have influenced prioritization of software requirements, identify the various types of artifacts proposed toward prioritizing software requirements, and examine certain characterizations of these artifacts. The results emphasize the heightened attention the domain of requirement prioritization has received in recent years. On the basis of this study, we are able to provide the following inferences regarding possible future research trajectories in software requirement prioritization artifacts: (1) focus on frameworks and tools; (2) emphasis on specialization; and (3) proposition of theory-based artifacts. Additional research possibilities are also pointed out at the end and are expected to stimulate further research on the topic. [ABSTRACT FROM AUTHOR]